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Proceedings Paper

Principled halftoning based on human vision models
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Paper Abstract

When models of human vision adequately measure the relative quality of candidate halftonings of an image, the problem of halftoning the image becomes equivalent to the search problem of finding a halftone that optimizes the quality metric. Because of the vast number of possible halftones, and the complexity of image quality measures, this principled approach has usually been put aside in favor of fast algorithms that seem to perform well. We find that the principled approach can lead to a range of useful halftoning algorithms, as we trade off speed for quality by varying the complexity of the quality measure and the thoroughness of the search. High quality halftones can be obtained reasonably quickly, for example, by using as a measure the vector length of the error image filtered by a contrast sensitivity function, and, as the search procedure the sequential adjustment of individual pixels to improve the quality measure. If computational resources permit, simulated annealing can find nearly optimal solutions.

Paper Details

Date Published: 27 August 1992
PDF: 13 pages
Proc. SPIE 1666, Human Vision, Visual Processing, and Digital Display III, (27 August 1992); doi: 10.1117/12.135960
Show Author Affiliations
Jeffrey B. Mulligan, NASA Ames Research Ctr. (United States)
Albert J. Ahumada, NASA Ames Research Ctr. (United States)


Published in SPIE Proceedings Vol. 1666:
Human Vision, Visual Processing, and Digital Display III
Bernice E. Rogowitz, Editor(s)

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